Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

Sunstone Weave: Local Semantic Code Search

by space-baconversion 0.1.2i★ –iRuns on your computer
Registry nameio.github.space-bacon/blackwindow-weave-mcp

Install

Overview

Description from the maker (original English)

Semantic search over local folders of code and docs, with a code-search encoder running on your CPU.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: BLACKWINDOW_WEAVE_CACHE

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "blackwindow-weave": {
      "command": "npx",
      "args": [
        "-y",
        "blackwindow-weave-mcp"
      ],
      "env": {
        "BLACKWINDOW_WEAVE_CACHE": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add blackwindow-weave --env BLACKWINDOW_WEAVE_CACHE=your-value -- npx -y blackwindow-weave-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "blackwindow-weave": {
      "command": "npx",
      "args": [
        "-y",
        "blackwindow-weave-mcp"
      ],
      "env": {
        "BLACKWINDOW_WEAVE_CACHE": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "blackwindow-weave": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "blackwindow-weave-mcp"
      ],
      "env": {
        "BLACKWINDOW_WEAVE_CACHE": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • BLACKWINDOW_WEAVE_CACHE env
    Where the encoder and the indexes are kept (default ~/.cache/blackwindow-weave, %USERPROFILE%\.cache\blackwindow-weave on Windows)

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account space-bacon, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 5671 servers in this category
  • Published to the registry more recently than 52% of the other 5671 servers in this category
  • Basic checks equal to or better than 100% of the other 5671 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Sunstone Weave: Local Semantic Code Search safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.2) reached the registry 38 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated 2 months ago
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

blackwindow-weave-mcp

Semantic search over the folders on your machine, for any MCP client. The server cuts source code and documentation into passages, embeds them with Motherlode, a 33M-parameter code-search encoder, on your CPU, and answers questions such as "where is a pairing line parsed into url, key and name" with file paths, line ranges and the passages themselves.

The only network requests are to huggingface.co on the first run: six requests, which leave five files, 133,752,819 bytes, in the cache. With the files cached, a run makes none.

This is the weave from Black Window and the Sunstone VS Code extension, packaged for clients that speak the Model Context Protocol. It runs on macOS, Linux and Windows with Node 20 or later.

Install

Install it once from a terminal, before adding it to a client. This installs the package and ONNX Runtime and prints the version once the runtime has loaded:

npx -y blackwindow-weave-mcp@0.1.2 --version

On GitHub's hosted runners, from an empty npm cache, this first install took 7 to 13 s on Linux and macOS and 55 to 69 s on Windows. Clients wait a limited time for a server to start (the MCP SDK's default is 60 s), and a client that stops waiting in the middle of an install can leave a broken copy in npm's cache (see Troubleshooting). Once installed, the server starts in under 3 s.

Keep the version in the client's configuration the same as here. With a version given, npx starts the copy it installed; with the bare name, npx (npm 11) looks for a newer version on every start and installs it while the client waits.

On Linux x64, ONNX Runtime also downloads 236 MB of CUDA libraries during the install. This server runs on the CPU and never loads them, so you can skip them:

ONNXRUNTIME_NODE_INSTALL=skip npx -y blackwindow-weave-mcp@0.1.2 --version

Add it to a client

macOS and Linux

Claude Code:

claude mcp add weave -- npx -y blackwindow-weave-mcp@0.1.2 --folder /path/to/your/repo

VS Code, in .vscode/mcp.json:

{

"servers": { "weave": { "type": "stdio", "command": "npx", "args": ["-y", "blackwindow-weave-mcp@0.1.2", "--folder", "${workspaceFolder}"] } } }

Cursor, Claude Desktop, Windsurf and most other clients:

{

"mcpServers": { "weave": { "command": "npx", "args": ["-y", "blackwindow-weave-mcp@0.1.2", "--folder", "/path/to/your/repo"] } } }

Windows

On Windows npx is a batch file, which a client can only start through cmd /c. Claude Code:

claude mcp add weave -- cmd /c npx -y blackwindow-weave-mcp@0.1.2 --folder C:\path\to\your\repo

Cursor, Claude Desktop, Windsurf and most other clients:

{

"mcpServers": { "weave": { "command": "cmd", "args": ["/c", "npx", "-y", "blackwindow-weave-mcp@0.1.2", "--folder", "C:/path/to/your/repo"] } } }

In VS Code the same command and args go under servers in .vscode/mcp.json, with "type": "stdio".

Installed globally

npm install -g blackwindow-weave-mcp@0.1.2 installs a blackwindow-weave-mcp command, which a client can start directly (cmd /c blackwindow-weave-mcp on Windows). To run from this repository instead of npm, replace blackwindow-weave-mcp@0.1.2 in the arguments with github:space-bacon/blackwindow-weave-mcp.

optionmeaning
--folder Weave this folder when the server starts. Repeatable. Optional: the model can call weave_folder itself.
--cache Where the encoder and the indexes live. Default ~/.cache/blackwindow-weave (on Windows %USERPROFILE%\.cache\blackwindow-weave), or BLACKWINDOW_WEAVE_CACHE.
--versionPrint the version and exit.

Platforms

Every push runs CI on Linux (x64 and arm64), Windows (x64) and macOS (Apple silicon), each with Node 20, 22 and 24. Each job runs the stdio smoke test below from a checkout. It then installs the packed package through npx from an empty npm cache, starts it the way a client does and weaves a folder. On Windows it also starts it through cmd /c. Last, it installs the package globally and starts it by its command. Other platforms, such as Windows on Arm, Intel Macs and Alpine Linux, are not tested.

Troubleshooting

The client times out when it first starts the server, or the server stops with `Cannot find module ... transformers.node.mjs`. A first install was interrupted, usually by a client that stopped waiting, and npm kept the half-installed copy. Delete npm's npx cache and install again from a terminal with the line under Install:

  • macOS and Linux: rm -rf ~/.npm/_npx
  • Windows (PowerShell): Remove-Item -Recurse -Force "$env:LOCALAPPDATA\npm-cache\_npx"

Updating. Install the new version from a terminal as above, then change the version in the client's configuration.

Tools

toolwhat it does
weave_folderIndex a folder, or bring its index up to date. Only files whose size or modification time changed are read again. A run longer than 25 s returns at once and continues in the background.
weave_searchThe passages nearest a plain-language or code query, with file, line range and score. Searches the folders woven in this session, or every woven folder if none was, or one folder when asked.
weave_listThe woven folders with their file and passage counts, and any weave still running.
weave_forgetDelete a folder's index. The folder's files are not touched.

Measured

On an Apple M2 Ultra (24 CPU cores, Node 24.4.1), through the MCP SDK's own stdio client, in test/smoke.mjs:

folderfilespassagesfirst weavesecond weavesearch
this package's src/6423.8 s, with the encoder's download0.013 s5 to 6 ms
the Sunstone repository571,36720.2 s0.014 s6 ms

Embedding runs at about 68 passages a second on that machine, so a repository of 10,000 passages takes about two and a half minutes the first time. Those figures are one run each on one machine. The smoke test's three questions about this package's own source each return the expected file first; they are a check that the pieces are wired together, not a measure of retrieval quality. For retrieval quality see the model card.

How it works

  • Files. A git work tree is listed by git, so .gitignore holds. Any other folder is walked, skipping node_modules, build output, virtual environments, lock files and minified files. Files over 1 MB and files that read as binary are skipped. JSON and XML are left out: in the Sunstone repository, result files under bench/results/ took ranks 2 and 3 of the question above when they were included.
  • Passages. Code is cut at definitions into passages of about 700 characters, each labelled with the nearest definition. Prose is cut at paragraphs and sentences into passages of about 420 characters. The chunkers are Black Window's.
  • Encoder. onnx/model.onnx (fp32) through transformers.js and ONNX Runtime on the CPU, CLS pooling.
  • Centring. Every vector has the model's shipped mean (centring/mean_shipped.json) subtracted and is brought back to unit length, so a score is a cosine after centring.
  • Search. Exact: every passage is scored. Before answering, a folder not checked in the last 30 s is brought up to date if fewer than 200 of its files changed; otherwise the answer says the index is stale.
  • Index. One per folder under /index/: a Float32 matrix and a JSONL of passages, named by a manifest that is written to a temporary file and renamed into place, so an interrupted write leaves the previous index. An index that cannot be read is moved aside rather than overwritten.

Licence

Business Source License 1.1 with an internal-use grant. You may use it for any internal purpose, including commercial development on your own or your employer's code, with no limit on seats. You may not offer it to others as a hosted search service or ship it inside a product you supply. On 15 September 2030 it becomes Apache-2.0. The encoder is downloaded under its own licence, which has the same shape. For other terms, write to burton@sunstonenorth.com.

Ask PopNx